Data Science Blog | Best Practices

Bringing ML to Agriculture: Transforming a Millennia-old Industry

Guest post by Jeff Melching from The Climate Corporation At The Climate Corporation, we aim to help farmers better understand their operations and...

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The importance of structure, coding style, and refactoring in notebooks

Notebooks are increasingly crucial in the data scientist's toolbox. Although considered relatively new, their history traces back to systems like...

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Data Science at The New York Times

Chris Wiggins, Chief Data Scientist at The New York Times, presented "Data Science at the New York Times" at Rev. Wiggins advocated that data...

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0.05 is an Arbitrary Cut Off: "Turning Fails into Wins”

Grace Tang, Data Scientist at Uber, presented insights, common pitfalls, and “best practices to ensure all experiments are useful” in her Strata...

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Best Practices for Managing Data Science at Scale

We recently published a practical guide for data science management intended to help current and aspiring managers learn from the challenges and...

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Emotional Intelligence for Data Science Teams

We surveyed and interviewed some of our most successful customers to learn how they align their data science team with their business. The challenges...

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What Data Scientists Should Know About Hiring, Sharing, and Collaborating

In this post we summarize some of our most recent and favorite answers on Quora to questions from the community about hiring junior data scientists,...

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Principles of Collaboration in Data Science

Data science is no longer a specialization of a single person or small group. It is now a key source of competitive advantage, and as a result, the...

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Introducing the Data Science Maturity Model

Many organizations have been underwhelmed by the return on their investment in data science. This is due to a narrow focus on tools, rather than a...

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The "Joel Test" for Data Science

It's the sixteenth anniversary of Joel Spolsky's "Joel Test," which he described as a "highly irresponsible, sloppy test to rate the quality of a...

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Reproducible Research in Computational Sciences

This guest post was written by Arnu Pretorius, a Masters student in Mathematical Statistics at the MIH Media Lab, Stellenbosch University. Arnu's...

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Data Science Platform: What is it? Why is it Important?

As more companies recognize the need for a [data science platform], more vendors are claiming they have one. Increasingly, we see companies...

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Providing Digital Provenance: from Modeling through Production

At last week's useR! R User conference, I spoke on digital provenance, the importance of reproducible research, and how Domino has solved many of the...

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Ugly Little Bits of the Data Science Process

This morning there was a great conversation on Twitter, kicked off by Hadley Wickham, about one of the ugly little bits of the data science process. ...

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